Rotator cuff disease is prevalent in the United States, with over 17 million individuals affected and accounting for over 3.8 million annual physician visits. Despite this, very limited information exists regarding its etiology. We have identified an increased risk for the development of rotator cuff disease utilizing the Utah Population Database (UPDB) which strongly suggests a genetic predisposition. Otherwise, there is limited data regarding a possible genetic role. Determining the genetic profile of rotator cuff disease could have profound effects on disease prevention and treatment. The purpose of this study is to create a powerful resource of patients diagnosed with full- thickness rotator cuff tears with DNA samples and complete phenotype data and to perform a genome-wide association analysis of these patients in order to identify genes and/or genetic variants associated with this disorder. Specific Aim 1: Recruit 500 study subjects over a 3-year period from a population of patients treated for rotator cuff tears by the principal investigator, an orthopaedic shoulder surgeon practicing at the University of Utah and the VA Hospital in Salt Lake City, UT. Subjects will include any patient with a MRI-confirmed full-thickness rotator cuff tear. All recruited subjects will undergo evaluation with a history, physical examination, documentation of demographic and family history, outcome questionnaire evaluation and blood sampling for genetic analysis. Specific Aim 2: Genotype all subjects and identify all genetic relationships between cases utilizing the UPDB to allow for appropriate correction in genetic analysis, and to allow comparison of clinical characteristics of familial cases of rotator cuff disease versus non-familial cases. All known genetic relationships of any of the rotator cuff disease patients will be integrated in order to ensure against any bias in the association analysis. Any case with at least one first or second degree relative also affected will be identified as a familial case and clinical characteristics (e.g. sex distribution, age distribution, injury severity, clinical outcomes) between familial and non-familial groups will be compared. Specific Aim 3: Perform a genome-wide case-control association analysis to determine chromosomal locations of associated predisposition genes and variants. All cases will be genotyped using the Illumina 610Q SNP marker set or equivalent high density marker set. Appropriate genomic-matched controls will be selected from the Illumina iControl publicly available data set. Correction for genetic relationships identified in Aim 2 will be made.